Vertex AI
Accelerating AI/ML Adoption In The Public Sector: Three Ways To Get Started
This is part one of a two-part series with practical tips to start your AI/ML journey. Machine learning (ML) and artificial intelligence (AI) are creating more personalized and easier digital experiences for constituents. According to recent studies, 92% of U.S. citizens1 report that improved digital services would positively impact their view of government. At the same …
MLOps System With AutoML And Pipeline In Vertex AI
When you build a machine learning product, you need to consider at least two MLOps scenarios. First of all, the model could be replaced later, as breakthrough algorithms are introduced in academia or industry. Secondly, the model itself has to evolve with the data in the changing world. We can handle both scenarios with the services provided …
Measuring Climate And Land Changes With AI
Imagine what could be possible if we had a dataset that could automatically and in near real-time show you how the Earth has changed week over week, month over month, year over year. We would get a birds eye view of recent events like floods, fires, snowstorms from days ago and be able to identify seasonal changes on the surface of the …
Reimagining AutoML With Google Research: Announcing Vertex AI Tabular Workflows
Earlier this year, we shared details about our collaboration with USAA, a leading provider of insurance and financial services to U.S. military members and veterans, who leveraged AutoML models to accelerate the claims process. Boasting a peak 28% improvement relative to baseline models, the automated solution USAA and Google Cloud produced can predict labor costs and …
Building AI In The Cloud: An Easier Way With Google Cloud And NVIDIA
NVIDIA GPU-powered instances on Google Cloud provide an optimal platform for organizations to develop their AI applications on the latest hardware and software stack, then seamlessly deploy those applications at scale in production. Simplifying Workflows to Speedup AI Developments NVIDIA recently announced the One Click Deploy feature on the NVIDIA NGC catalog, the hub for GPU-optimized …
Google Is named A Leader In The 2022 Gartner® Magic Quadrant™ For Cloud AI Developer Services Report
Gartner® named Google as a Leader in the 2022 Magic Quadrant™ for Cloud AI Developer Services report. This evaluation covered Google’s language, vision and structured data products including AutoML, all of which we deliver through Google Cloud. We believe this recognition is a reflection of the confidence and satisfaction that customers have in our language, …
Epidemic Sound Launches AI Audio-Based Search Tool On Google Cloud
Epidemic Sound, the market-leading service for direct licensing of royalty-free music, today announced Epidemic Audio Reference (EAR), an audio-based search tool running on Google Cloud that will help content creators quickly and easily find music for their productions. Epidemic Sound offers 35,000 tracks and 90,000 sound effects used by millions of storytellers worldwide – everyone …
How AI-Curated Suggestions Serve A Better Client Experience At Richemont
Whether they meet customers online, offline, or in some combination, retailers share a big problem: How can they offer the right choices, when and how the customer wants, without overwhelming (and often losing) the buyer? More than anything, this is an information problem. As such, it’s a good candidate for using artificial intelligence (AI) for …
Using Vertex AI For Rapid Model Prototyping And Deployment
Bringing AI models to a production environment is one of the biggest challenges of AI practitioners. Much of the discussions in the AI/ML space revolve around model development. As shown in this diagram from the canonical Google paper “Hidden Technical Debt in Machine Learning Systems”, the bulk of activities, time and expense in building and …
Building Continuous Integration & Continuous Delivery For Autonomous Vehicles On Google Cloud
San Francisco’s roads are a notoriously tough place for people to drive. Narrow streets, busy pedestrian traffic, and an extensive network of bicycle routes make driving through San Francisco roughly 40 times more complex than driving in a suburban environment, according to Cruise data. This level of complexity makes San Francisco, America’s second densest city, …